Factorial analysis on forest canopy density restoration in the burned area of northern Great Xing＇an Mountains, China

The restoration of forest landscape has drawn much attention since thecatastrophic fire took place on the northern slope of Great Xing'an Mountains in 1987. Forest canopydensity, which has close relation to forest productivity, was selected as a key factor to find howmuch the forest quality was changed 13 years after fire, and how fire severity, regeneration way andterrain factors influenced the restoration of forest canopy density, based on forest inventory datain China, and using Kendall Bivariate Correlation Analysis, and Distances Correlation Analysis. Theresults showed that fire severity which was inversely correlated with forest canopy density gradewas an initial factor among all that selected. Regeneration way which did not remarkably affectforest canopy density restoration in short period, may shorten the cycle of forest succession andpromote the forest productivity of conophorium in the future. Among the three terrain factors, theeffect of slope was the strongest, the position on slope was the second and the aspect was the last.

Study on seismic performance enhancement in bridges based on factorial analysis

The seismic performance of bridges depends on the ductile behavior of its column, as the deck and other substructural components except pile foundations are normally designed to be elastic to facilitate bridge retrofitting. Codes such as AASHTO, Caltrans, IRC： 112 etc. give guidelines for the seismic performance enhancement of columns through ductile detailing. In the present study, a methodology for the seismic performance enhancement of bridges is discussed by using a ＂Parameter-Based Influence Factor＂ （PIF） developed from factorial analysis. The parameters considered in the factorial analysis are： percentage of longitudinal reinforcement （Pt）, compressive strength of concrete （f＇c）, yield strength of steel （fy）, spacing of lateral ties （5） and column height （/4）. The influence of each parameter and their combination on the limit states considered is estimated. Pushover analysis is used to evaluate the capacity of columns, considering shear failure criteria. A total of 243 （35 combinations） analysis results are compiled to develop ＇PIF＇ used in the performance enhancement process. The study also encompasses other sub-objectives such as evaluating the discrepancies in using the Importance Factor （/） in designing bridges of varied functional importance; and estimating the aspect ratio and slenderness ratio values of bridge columns for its initial sizing.

Development of a random-forest-copula-factorial analysis(RFCFA)method for predicting propagation between meteorological and hydrological drought

In the context of global climate warming,the propagation of meteorological drought(MD)may aggravate the devastating impact of hydrological drought(HD)on water security and sustainable development.There are challenges in accurately predicting the propagation of drought and effectively quantifying the effects of uncertainty,especially in data-deficient regions.In this study,a novel method called RFCFA is developed through integrating random forest(RF),copula,and factorial analysis(FA)into a general framework as well as applied to the Aral Sea Basin(a typical arid and data-scarce basin in Central Asia)under considering the impact of climate change.Several findings can be summarized:(1)the projected future drought propagation probability of ASB is 39.2%,which is about 8%higher than historical level;(2)drought propagation is mainly affected by mean climate condition,catchment characteristics(i.e.,elevation,LUCC,and slope),and human activities(i.e.,irrigation and reservoir operation);(3)the lower propagation probability in spring is expected under SSP1-2.6 due to increased snow meltwater,and the drought propagation probability in autumn is the highest(reaching 45.4%)under the influence of reservoir operation;(4)the combined effects of meteorological conditions and agricultural irrigation can lead to a higher probability of future propagation in the upper river basin in summer.Findings are valuable for predicting drought propagation risk,revealing main factors and inherent uncertainties,as well as providing support for drought management and disaster prevention.

The spatial multiscale variability of heavy metals based on factorial kriging analysis: A case study in the northeastern Beibu Gulf

Factorial kriging analysis is applied to the research on the spatial multiscale variability of heavy metals in submarine. It is used to analyze the multiscale spatial structures of seven heavy metals, Ni, Cu, Zn, Pb, Cr, As and Cd in the surface sediment from the northeastern of Beibu Gulf, identify and separate spatial variations at different scales of heavy metals, and discuss the provenance of heavy metals and the influencing factors. The results show that the existence of three-scale spatial variations those consist of nugget effect, a spherical structure with range of 30 km（short-range scale） and a spherical structure with range of 140 km（long-range scale） in the linear model of coregionalization fitted. The spatial distribution features of seven heavy metals at short-range scale reflect ＂spot-like＂ or ＂stripe-like＂ local-scale spatial variations; the spatial distribution features of the seven heavy metals at long-range scale represent ＂slice-like＂ regional-scale spatial variations. At local scale, Zn, Cr, Ni,Cu, Pb and Cd are derived primarily from parent materials of Hainan Island, Leizhou Peninsula and Guangxi land, whose spatial distribution characteristics are controlled by granularity of sediments, while As is influenced dominantly by human pollution components from Hainan Island and Leizhou Peninsula. At regional scale, Zn,Cr, Ni and Cu originate primarily from parent rock materials of Leizhou Peninsula and Hainan Island, secondly from Guangxi land; As originated primarily from parent rock materials from Hainan Island, secondly from Leizhou Peninsula and Guangxi land. These metals are transported and migrated with sediments dominated by the anticlockwise circulation of Beibu Gulf year-round, deposited in ＂convergence center＂, forming the whole sedimentary pattern in direction of NWW-NNW at regional scale. The difference in distribution type between As and other metals at regional scale is mainly due to their different geochemical behavior.

A Quantitative Factorial Component Analysis to Investigate the Recent Changes of Japan’s Weight-Based Food Self-Sufficiency Ratio

We investigate the weight-based food self-sufficiency ratio (WSSR) for Japan over a 50-year period (1961-2011) by applying factorial component analysis technique in order to measure the changes of the WSSR quantitatively. Quantitative data analysis is employed to determine the drivers of those changes. Numerical results show that Japan experienced a drastic decline in its food self-sufficiency ratio (FSSR) during the above period. The factorial component analysis shows that such a decline was caused by the changes in the FSSR of the food groups/items, not in the quantity of the food supply. A number of characteristics of those changes are presented and a list of major food groups that have major impacts on the changes is constructed. The findings in this paper reiterate the alarming food security problem in Japan and provide clear insight into the causes of this problem. The findings in this study pick up where previous studies have left off, aid the food-related policy-making process and identify new ideas for future food research.

Elaboration of Explanatory Factors of Accidents in Cameroon by Factorial Correspondence Analysis

The aim of this paper is to examine the causes of road accidents in Cameroon. The Douala-Yaoundé highway was chosen as the case of study. Available field data recorded from the year 2006 to 2011, have enabled the analysis of each accident. The method used here is the factorial correspondence analysis;which aims to bring in a small number of dimensions, most of the initial information, focusing not on the absolute values, but the correspondence between the variables, that is to say the relative values. From this analysis, it appears that, of the 906 accidents recorded during this period, top five causes account for nearly 83% of the information provided by the set of variables on the occurrence of road accidents. These causes are: driver inattention, lack of control, over speeding, improper overtaking and tire puncture. These results require involvement in the construction of road safety policies through training, sensitization and adequate repressions as well as administrative reforms and research policy in road safety.

Coupling Discriminating Statistical Analysis and Artificial Intelligence for Geotechnical Characterization of the Kampemba’s Municipality Soils (Lubumbashi, DR Congo)

This study focuses on the determination of physical and mechanical characteristics based on in vitro tests, by using field samples for the Kampemba urban area in the city of Lubumbashi. At the end of this study, we identified the soils according to their parameters, and established the geotechnical classification by determining their bearing capacity by the group index method using from the identification tests carried out. By using the AASHTO classification method (American Association for State Highway Transportation Official), the results obtained after our studies revealed five classes of soil: A-2, A-4, A-5, A-6, A-7 in a general way, and particularly eight subgroups of soil: A-2-4, A-2-6, A-2-7, A-4, A-5, A-6, A-7-5 and A-7-6 for the concerned area. The latter has given statistical analysis and deep learning based on multi-layer perceptron, the global values of the physical parameters. It’s about: 31.77% ± 1.05% for the limit of liquidity;18.71% ± 0.76% for the plastic limit;13.06% ± 0.79% for the plasticity index;83.00% ± 3.33% for passing of 2 mm sieve;76.22% ± 3.2% for passing of 400 μm sieve;89.07% ± 2.99% for passing of 4.75 mm sieve;70.62% ± 2.39% passing of 80 μm sieve;1.66 ± 0.61 for the consistency index;−0.67 ± 0.62 for the liquidity index and 8 ± 1 for the group index.

Anthropozoic impact on the floristic biodiversity in the area of Beni Saf(Algeria)

The degradation of the natural resources in Algeria nowadays remains a major constraint for the agrosilvopastoral development. Indeed, the area of Beni Saf is confronted with many problems such as the anthropozoic pressure which does not make it possible to keep balance between the exploitation of the natural resources and their regenerations in time and space. Following the example results obtained through a floristic study by the factorial analysis of correspondences (F A C), concerning the identification of anthropozoogenes species such as: Chamaerops humilis, Asphodelus microcarpus, Withania frutescens, Calycotome spinosa, Asparagus albus;furthermore, the calculation of the disturbance index which marks the rate of therophytisation which is about 68%, that one finds it very high. These indices show a disturbance and an imbalance of the plant formation of the zone of study, caused by the high anthropozoogene pressure. Vis-a-vis this threat, it is essential to propose a possibility of intervention for a durable management of these spaces.

Detailed parametric design methodology for hydrodynamics of liquid-solid circulating fluidized bed using design of experiments

A design-of-experiments methodology is used to develop a statistical model for the prediction of the hydrodynamics of a liquid–solid circulating fluidized bed. To illustrate the multilevel factorial design approach, a step by step methodology is taken to study the effects of the interactions among the independent factors considered on the performance variables. A multilevel full factorial design with three levels of the two factors and five levels of the third factor has been studied. Various statistical models such as the linear, two-factor interaction, quadratic, and cubic models are tested. The model has been developed to predict responses, viz., average solids holdup and solids circulation rate. The validity of the developed regression model is verified using the analysis of variance. Furthermore, the model developed was compared with an experimental dataset to assess its adequacy and reliability. This detailed statistical design methodology for non-linear systems considered here provides a very important tool for design and optimization in a cost-effective approach

Metallic wastewater treatment by sulfate reduction using anaerobic rotating biological contactor reactor under high metal loading conditions

This study was aimed at investigating the performance of anaerobic rotating biological cont- reactor treating synthetic wastewater containing a mixture of heavy metals under sulfate redu condition. Statistically valid factorial design of experiments was carried out to understand dynamics of metal removal using this bioreactor system. Copper removal was maximum （〉98% followed by other heavy metals at their respective low inlet concentrations. Metal loading rates than 3.7 mg/L· h in case of Cu（II）; less than 1.69 mg/L· h for Ni（II）, Pb（II）, Zn（II）, Fe（III） and C are favorable to the performance of the An-RBC reactor. Removal efficiency of the heavy metals 1 mixture depended on the metal species and their inlet loading concentrations. Analysis of n precipitates formed in the sulfidogenic bioreactor by field emission scanning electron microscopyalong with energy dispersive X-ray spectroscopy （FESEM-EDX） confirmed metal sulfide precipitationby SRB. All these results clearly revealed that the attached growth biofilm bioreactor is well suited for heavy metal removal from complex mixture.